Querying Databricks Apache Iceberg Tables with the Borderless Lakehouse
Google, Thursday, October 29th, 2026
Google's borderless Lakehouse lets BigQuery query Databricks-managed Apache Iceberg tables in place without copying data.
BigQuery reads the same files Databricks writes, and changes appear after the next scheduled metadata refresh, as often as every 5 minutes.
Managed Iceberg tables generate Iceberg-compatible metadata alongside Delta logs, so teams store Parquet files once in Google Cloud Storage and apply BigQuery's vectorized engine directly.
The approach avoids duplicated storage cost, latency and fragmented security controls.
Federation extends to Amazon S3 and Azure Blob Storage through the open Iceberg REST catalog.